Citizen Science and Geospatial Capacity Building

• Other Authors: Kocaman, Sultan (Editor), Saran, Sameer (Editor), Durmaz, Murat (Editor), Kumar, A. (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Subjects: Research & information: general; participatory toponyms; knowledge sharing; public participation; citizen science; geospatial capacity building; volunteered geographic information; social media; spatiotemporal bias; CitSci; earthquake; intensity mapping; disaster mitigation; spatial kriging; volunteered geographic information (VGI); data contribution activities; spatial and temporal patterns; biases; eBird; community-based geoportal; crowdsourced earth observation product; remote sensing; spatial data infrastructure (SDI); crowdsourced data quality; GeoWeb; outdoor air pollution; symptom mapping; data quality; web application; water quality; community-based monitoring; machine learning; Indian monsoon; Jacobin cuckoo; Maxent; species distribution model; habitat suitability; range expansion; WorldClim; CMIP; crowdsourcing; participatory GIS
• Online Access: DOAB: download the publication; DOAB: description of the publication

This book is a collection of the articles published the Special Issue of ISPRS International Journal of Geo-Information on "Citizen Science and Geospatial Capacity Building". The articles cover a wide range of topics regarding the applications of citizen science from a geospatial technology perspective. Several applications show the importance of Citizen Science (CitSci) and volunteered geographic information (VGI) in various stages of geodata collection, processing, analysis and visualization; and for demonstrating the capabilities, which are covered in the book. Particular emphasis is given to various problems encountered in the CitSci and VGI projects with a geospatial aspect, such as platform, tool and interface design, ontology development, spatial analysis and data quality assessment. The book also points out the needs and future research directions in these subjects, such as; (a) data quality issues especially in the light of big data; (b) ontology studies for geospatial data suited for diverse user backgrounds, data integration, and sharing; (c) development of machine learning and artificial intelligence based online tools for pattern recognition and object identification using existing repositories of CitSci and VGI projects; and (d) open science and open data practices for increasing the efficiency, decreasing the redundancy, and acknowledgement of all stakeholders.